7 Quick Takes (7/23/10)

7 Quick Takes (7/23/10) July 23, 2010


The universe has seen fit to give me an excellent birthday present this year.  On Wednesday, I discovered this video of my new favorite machine in the whole world: a train that lays its own tracks!  I am a total eight-year-old boy when it comes to big noisy machines.  Pity the person who got stuck behind me on a narrow escalator the other day.  The escalator next to ours was being repaired, so I stopped walking and hung halfway over the rail trying to get a good look at the guts of the escalator.  Other favorite eight-year-old boy pursuits I have enjoyed in the last week: standing on top of BIG THINGS and making things LIGHT UP.



Another excellent birthday present came from my mom, who gave me Edward Tufte’s classic handbook: The Visual Display of Quantitative Information.  In Tufte’s spirit, I want to highlight a great visualization from the much discussed Pew study on changes in religious affiliation. (h/t Common Sense Atheism)



Here’s another fascinating visualization for your perusal: Designer Michæl Paukner’s illustration of the ancient Hebrew idea of the structure of the cosmos. (h/t io9).  And one more high class visualization: the Lagoa simulator for modeling beautiful physics.



Interesting data analysis can start anywhere!  Online dating site OKCupid uses anonymized user data to study  revealed preferences of suitors and the effectiveness of different online approaches.  One recent fascinating post explored what lies were most common among users.  (One interesting finding: men inflate their height about two inches on average, but there’s also a clear preference to list your height at 6 feet even, skewing the distribution).



Now if only the US Government had the same delight in data as do the people linked above.  This week I have an article up for the Huffington Post on the way a lack of reliable statistics leads to a lack of accountability. [If you’re checking this in the very early morning, the article won’t be live til around 10am).

Well. that was overly optimistic.  I’m still stuck on a conclusion and a title, and, since I don’t want to bury it in the weekend, the piece won’t be up til Monday.



Just a reminder: BlagHag is running her annual blogathon on July 31st.  She’ll be posting every half hour for 24 hours to raise money for the Secular Students Alliance.  You can pledge a lump sum or make a wacky pledge keyed to how ofter she uses a particular word in the posts or any other criteria you like.



I didn’t plan for this to be a data and statistics centered 7 Quick Takes.  What a delightful surprise for us all!  Here’s a great capper to the list.

Check out this great post “So you think you’re a Bayesian” on Less Wrong.  It gives a nice introduction to the difference between frequentist (boo!) and Bayesian (woo!) statistics and used clear examples to show how people frequently (and wrongly) default to frequentist thinking.  Here’s the first question. Click on the link above to read the explanation.

Linda is 31 years old, single, outspoken and very bright. She majored in philosophy. As a student, she was deeply concerned with issues of discrimination and social justice, and also participated in antinuclear demonstrations.

Which is more likely?

(a) Linda is a bank teller

(b) Linda is a bank teller and active in the feminist movement



[Seven Quick Things is a blog carnival run by Jen of Conversion Diary]

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  • NFQ

    Happy (belated?) birthday!re: #4, if you like OkCupid data, you'll have a field day with this — http://contexts.org/socimages/?s=okcupid (if you haven't already seen all that stuff before). The accompanying sociological analysis is nice, even if you've seen the graphs, at least IMHO.I really love the example you quote in #7. It's such an effective way of calling these sorts of issues to your attention.

  • My husband will l.o.v.e. that train that lays its own tracks. He's an 8-year-old-boy too when it comes to trains and construction.

  • 1) I had no idea that Hayek had advanced the connectionist theory of the mind. Weird…2) Why boo frequentism? I routinely use Bayesian classifiers at work, but the naughty secret is that their utility is explained perfectly well by frequentist statistics.What additional explanatory power does Bayesianism provide? If none, how do you reconcile this apparently metaphysical belief with your broader positivism?

  • The main problem with frequentism is that people see it as valid only when there is a clearly understood sample space. When HS teaches students that you do probability by counting all possible outcomes and counting instances of the particular outcome and then dividing, it limits the way they think about probability as a way of making sense of uncertainty.